We analyzed a network sample containing functional connectivity matrices from 50 schizophrenia patients (40 paranoid type and 10 residual type), and 72 healthy controls. Preprocessed fMRI data are publicly available from the 1000 connectomes project by the Center for Biomedical Research Excellence (COBRE) (http://fcon_1000.projects.nitrc.org/indi/retro/cobre.html). To construct the network sample of functional connectivity matrices, we use a previously validated atlas – the power atlas [1]} – that specifies 264 spheres of radius 8mm, which constitute our 264 regions of interest (ROIs). We averaged the fMRI time series from all voxels within each ROI, yielding 264 time series per participant. For each of these time series, we regressed out 6 motion parameters accounting for head movement, 4 parameters corresponding to cerebrospinal fluid, and 4 parameters corresponding to white matter. For each individual in the study, we constructed a functional connectivity network by first calculating the Pearson correlation of each pair of ROIs. We placed an edge between all ROIs that had a correlation in the top 10% of correlation between pairs of ROIs in the matrix. This gave a network sample of 122 functional connectivity networks of which 72 were healthy controls and the remaining 50 were patients with schizophrenia. More information on the collection, scanning parameters, and preprocessing of the COBRE data is provided in the Appendix.
